[Air-L] Call for Tutorials: ACM FAT* 2019 (ACM Conference on Fairness, Accountability, and Transparency)

Veale, Michael m.veale at ucl.ac.uk
Sun Sep 2 14:06:54 PDT 2018


Could you deliver a session that would further practice and knowledge around societal implication and risks of algorithmic systems? The second ACM Conference on Fairness, Accountability, and Transparency (ACM FAT* 2019) is soliciting a wide variety of tutorials to be delivered on January 29, 2019 in Atlanta, Georgia.

- *Hands-on Tutorials*  (90 or 180 mins) should give ACM FAT*’s broad audience the chance to experiment with new software packages to deal with the issues of the conference.

- *Translation Tutorials* (45 or 90 mins) aim to "translate" between disciplines; for instance, by explaining computer science concepts in a way that will be practically useful for lawyers, policy makers, and other practitioners, or by explaining legal, policy, or social science concepts in a way that will guide computer scientists in their future technical explorations.

- *Implications Tutorials* (45 or 90 mins) should cover known legal, policy, medical, or socio-economic effects of unfair algorithmic systems, lack of interpretability of machine learning models, biases in the data, or other ACM FAT* related issues. We particularly encourage submissions by civil rights lawyers, policy advocates, civil society representatives, and others who work closely with individuals and communities affected by algorithmic systems.

3 page tutorial descriptions (+1 page for Hands-On Tutorials), are due September 13, 23:59 AoE Time, and those successful will be notified on October 15.

More information, including more detailed information about formats and types of session, is available here: https://fatconference.org/2019/cftutorials.html

Best wishes,

Michael and Michael
Publicity Co-Chairs, ACM FAT* 2019
--
Michael Veale [@mikarv<https://twitter.com/mikarv>, http://michae.lv<http://michae.lv/>]
Dept. of Science, Technology, Engineering & Public Policy
University College London
+44(0)2031089736



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